Optimising quantity of manufacturing and remanufacturing in an electric vehicle battery closed-loop supply chain

Purpose: Batteries installed on electric vehicles (EVs) should normally be removed when their capacity falls to 70-80 per cent, but they are still usable for other purposes, such as energy storage. This paper studies an EV battery closed-loop supply chain (CLSC) consisting of a battery manufacturer and a remanufacturer. The manufacturer produces new batteries by using natural resources, while the remanufacturer collects returned batteries and makes decisions based on the return quality, that is, to reuse or recycle. The purpose of this paper is to maximise the individual profits through optimising the amount of manufacturing and remanufacturing, respectively, and optimising the purchase price of returned batteries. Design/methodology/approach: Based on the Nash equilibrium, this paper develops a three-period model in the CLSC. In period 1, batteries are made from raw materials; in period 2, returned batteries from period 1 are sorted into low quality and high quality. Some high-quality returns can be reused for other purposes while those non-reusable returns are recycled into materials. In period 3, all the returns are recycled into materials. The analytical results are derived. Findings: The result of the analyses suggest that first, among the variables that affect the (re)manufacturing decision, the purchase price for returned batteries plays a critical role. In particular, the price of low-quality returns has more influence than the price of high quality returns. Second, the higher purchase price for re-usable returns does not necessarily lead to a higher return rate of reusable returns. Third, the manufacturer’s profit is normally higher than the remanufacturer’s. This suggests the need to design incentives to promote the remanufacturing sector. And finally, although it is appreciated that maximising the utilisation of batteries over the life-cycle would benefit the environment, the economic benefit needs further investigation. Originality/value: Although the CLSC has been widely studied, studies on the EV battery CLSC are scarce. The EV battery CLSC is particularly challenging in terms of the reusability of returns because used EV batteries cannot be reused for the original purpose, which complicates CLSC operations. This paper explores the interrelationship between manufacturer and remanufacturer, explaining the reasons why recycling is still underdeveloped, and suggests the possibility of enhancing remanufacturing profitability

Sustainable consumption and production in emerging markets

This special issue addresses sustainable consumption and production (SCP) in emerging markets by examining novel methods, practices, and opportunities. The articles present and analyze top-down sustainability efforts as well as bottom-up efforts on firms, supply chain networks, government regulations, and solution methods. This editorial note summarizes the discussions on the firm's operational attributes, sustainable consumption and production practices, and on evaluation and implementation methods. A dominant finding is that the issues of SCP should be explored in different ways within different contexts in emerging countries

A framework for evaluating the performance of sustainable service supply chain management under uncertainty

Developing and accessing a measure of sustainable service supply chain management (SSSCM) performance is currently a key challenge. The main contributions of this study are two-fold. First, this paper provides valuable support for SSSCM regarding the nature of network hierarchical relations with qualitative and quantitative scales. Second, this study indicates the practical implementation and enhances management effectiveness for SSSCM. The literature on SSSCM is very limited and performance measures need to have a systematic framework. The purpose of this study is to develop and evaluate the SSSCM importance based on aspects i.e., environmentally conscious design, environmental service operations design and environmentally sustainable design. This paper developed a hierarchical network for SSSCM in a closed-loop hierarchical structure. A generalized quantitative evaluation model based on the Fuzzy Delphi Method and Analytical Network Process were then used to consider both the interdependence among measures and the fuzziness of subjective measures in SSSCM. The results indicate that the top-ranking aspect to consider is that of environmental service operation design, and the top criteria is reverse logistics integrated into service packag

Knowledge management in sustainable supply chain management: improving performance through an interpretive structural modelling approach

Sustainable supply chain management is one vital element in achieving competitive advantage in business management and knowledge management is seen to be one key enabler. However, in previous studies the interrelationships between knowledge management and sustainable supply chain management are still under-explored. This study proposes a set of measures and interpretive structural modelling methods to identify the driving and dependence powers in sustainable supply chain management within the context of knowledge management, so as to improve the performance of firms from the textile industry in Vietnam. The research result indicated that learning organisation, information/knowledge sharing, joint knowledge creation, information technology and knowledge storage are amongst the highest driving and dependence powers. These attributes are deemed to be most-effective to enhance the performance of firms. To further enhance the value of this research, theoretical and managerial implications are also discussed in this study

Toward Sustainability:Using Big Data to Explore Decisive Supply Chain Risk Factors Under Uncertainty

Rapid market changes aimed at sustainability have led to supply chain risks and uncertainties in the Taiwanese light-emitting diode industry. These risks and uncertainties can be captured by social media, quantitative and qualitative data (referred to herein as big data), but the industry has been unable to manage this information boom to respond to customer needs. These various types of data have their own characteristics that affect decision making about developing firm capabilities. This study aggregates the various data to undertake an extensive investigation of supply chain risks and uncertainties. Specifically, this study proposes using the fuzzy and grey Delphi methods to identify a set of reliable attributes and, based on these attributes, transforming big data to a manageable scale to consider their impacts. Subsequently, both the fuzzy and grey Decision Making Trial and Evaluation Laboratories applied to determine the causal relationships for supply chain risks and uncertainties. The results reveal that capacity and operations have greater influence than other supply chain attributes and that risks stemming from triggering events are difficult to diagnose and control. The implications, conclusions and findings are addressed

Using big data to make better decisions in the digital economy

The question this special issue would like to address is how to harvest big data to help decision-makers to deliver better fact-based decisions aimed at improving performance or to create better strategy? This special issue focuses on the big data applications in supporting operations decisions, including advanced research on decision models and tools for the digital economy. Responds to this special issue was great and we have included many high-quality papers. We are pleased to present 13 of the best papers. The techniques presented include data mining, simulation and expert system with applications span across online reviews, food retail chain to e-health

Anomaly Cancellation and Smooth Non-Kahler Solutions in Heterotic String Theory

We show that six-dimensional backgrounds that are T^2 bundle over a Calabi-Yau two-fold base are consistent smooth solutions of heterotic flux compactifications. We emphasize the importance of the anomaly cancellation condition which can only be satisfied if the base is K3 while a T^4 base is excluded. The conditions imposed by anomaly cancellation for the T^2 bundle structure, the dilaton field, and the holomorphic stable bundles are analyzed and the solutions determined. Applying duality, we check the consistency of the anomaly cancellation constraints with those for flux backgrounds of M-theory on eight-manifolds.Comment: 30 pages, harvmac; v2: typos corrected and minor clarifications adde

Heart rate variability and target organ damage in hypertensive patients

Background: We evaluated the association between linear standard Heart Rate Variability (HRV) measures and vascular, renal and cardiac target organ damage (TOD). Methods: A retrospective analysis was performed including 200 patients registered in the Regione Campania network (aged 62.4 ± 12, male 64%). HRV analysis was performed by 24-h holter ECG. Renal damage was assessed by estimated glomerular filtration rate (eGFR), vascular damage by carotid intima-media thickness (IMT), and cardiac damage by left ventricular mass index. Results: Significantly lower values of the ratio of low to high frequency power (LF/HF) were found in the patients with moderate or severe eGFR (p-value < 0.001). Similarly, depressed values of indexes of the overall autonomic modulation on heart were found in patients with plaque compared to those with a normal IMT (p-value <0.05). These associations remained significant after adjustment for other factors known to contribute to the development of target organ damage, such as age. Moreover, depressed LF/HF was found also in patients with left ventricular hypertrophy but this association was not significant after adjustment for other factors. Conclusions: Depressed HRV appeared to be associated with vascular and renal TOD, suggesting the involvement of autonomic imbalance in the TOD. However, as the mechanisms by which abnormal autonomic balance may lead to TOD, and, particularly, to renal organ damage are not clearly known, further prospective studies with longitudinal design are needed to determine the association between HRV and the development of TOD

Analysis of Degradation of Sb2Se3 Thin Film Solar Cells Deploying a Time-Dependent Approach Linked with 1D-AMPS Simulation

In this paper, we have developed a time-dependent model to study defect growth in the absorber layer of Sb2Se3 thin film solar cells. This model has been integrated with the AMPS-1D simulation platform to investigate the impact of increasing defect density at different positions within the Sb2Se3 layer on the electrical parameters of the solar cell. We adopted the Gloeckler standard model for thin films in AMPS to represent Sb2Se3 materials. The study focuses on tracking the degradation of device performance parameters as donor-like mid-gap states accumulate in the Sb2Se3 layer over time. We monitored the variation of key electrical parameters, including efficiency (η), fill factor (FF), open-circuit voltage (Voc), and short-circuit current (Jsc), at three different positions: the interface with CdS, the bulk of the Sb2Se3 layer, and the interface with the top contact. These positions are susceptible to increasing defect density during prolonged operation and irradiation. To pinpoint the most sensitive part of the Sb2Se3 layer to defect accumulation, we divided the layer into three sub-layers. Our simulation results highlight that the CdS/Sb2Se3 interface is the most vulnerable position in the cell when it comes to defect accumulation. The practical implication of this study is that special attention should be given to the CdS/Sb2Se3 interface during material deposition and the development of high-stability Sb2Se3 thin film solar cells.